Data compression occurs in a number of contexts. It is very commonly used in communications and computer networking to store, transmit, and reproduce information efficiently. It finds particular application in the encoding of images, audio and video. Video presents a significant challenge to data compression because of the large amount of data required for each video frame and the speed with which encoding and decoding often needs to occur. The current state-of-the-art for video encoding is the ITU-T H.264/AVC video coding standard. It defines a number of different profiles for different applications, including the Main profile, Baseline profile and others. A next-generation video encoding standard is currently under development through a joint initiative of MPEG-ITU termed High Efficiency Video Coding (HEVC). The initiative may eventually result in a video-coding standard commonly referred to as MPEG-H.
There are a number of standards for encoding/decoding images and videos, including H.264, that use block-based coding processes. In these processes, the image or frame is divided into blocks, typically 4×4 or 8×8, and the blocks are spectrally transformed into coefficients, quantized, and entropy encoded. In many cases, the data being transformed is not the actual pixel data, but is residual data following a prediction operation. Predictions can be intra-frame, i.e. block-to-block within the frame/image, or inter-frame, i.e. between frames (also called motion prediction). It is expected that MPEG-H will also have these features.
When spectrally transforming residual data, many of these standards prescribe the use of a discrete cosine transform (DCT) or some variant thereon. The resulting DCT coefficients are then quantized using a quantizer to produce quantized transform domain coefficients, or indices.
The block or matrix of quantized transform domain coefficients (sometimes referred to as a “transform unit”) is then entropy encoded using a particular context model. In H.264/AVC and in the current development work for MPEG-H, the quantized transform coefficients are encoded by (a) encoding a last significant coefficient position indicating the location of the last non-zero coefficient in the transform unit, (b) encoding a significance map indicating the positions in the transform unit (other than the last significant coefficient position) that contain non-zero coefficients, (c) encoding the magnitudes of the non-zero coefficients, and (d) encoding the signs of the non-zero coefficients. This encoding of the quantized transform coefficients often occupies 30-80% of the encoded data in the bitstream.
Transform units are typically N×N. Common sizes include 4×4, 8×8, 16×16, and 32×32, although other sizes are possible, including non-square sizes in some embodiments, such as 16×4, 4×16, 8×32 or 32×8. The entropy encoding of the symbols in the significance map is based upon a context model. In the case of 4×4 or 8×8 luma or chroma blocks or transform units (TU), a separate context is associated with each coefficient position in the TU. The encoder and decoder must keep track of and look up a large number of different contexts during the encoding and decoding of the significance map. In the case of larger TUs, the context for encoding a significant flag may depend on the values of neighboring significance flags. For example, the flag may have a context selected from four or five contexts depending on the values of neighboring flags. In some instances, particular flags within a TU or sub-block of a TU may have a context based on position, such as the upper-left (DC) position.
Similar reference numerals may have been used in different figures to denote similar components.